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・ Construction of Assembly Hall (Champaign)
・ Construction of Concept Map
・ Construction of electronic cigarettes
・ Construction of Mount Rushmore
・ Construction of One World Trade Center
・ Constrained generalized inverse
・ Constrained geometry complex
・ Constrained optimization
・ Constrained Shortest Path First
・ Constrained writing
・ Constrained-layer damping
・ Constraint
・ Constraint (classical mechanics)
・ Constraint (computer-aided design)
・ Constraint (information theory)
Constraint (mathematics)
・ Constraint algebra
・ Constraint algorithm
・ Constraint automaton
・ Constraint Composite Graph
・ Constraint counting
・ Constraint Grammar
・ Constraint graph
・ Constraint graph (layout)
・ Constraint Handling Rules
・ Constraint inference
・ Constraint learning
・ Constraint logic programming
・ Constraint programming
・ Constraint satisfaction


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Constraint (mathematics) : ウィキペディア英語版
Constraint (mathematics)

In mathematics, a constraint is a condition of an optimization problem that the solution must satisfy. There are several types of constraints—primarily equality constraints, inequality constraints, and integer constraints. The set of candidate solutions that satisfy all constraints is called the feasible set.
==Example==
The following is a simple optimization problem
:\min f(\bold x) = x_1^2+x_2vf^4
\text
x_1 \ge 1
\text
x_2 = 1

where \bold x denotes the vector (x1, x2).
In this example, the first line defines the function to be minimized (called the objective function, loss function, or cost function). The second and third lines define two constraints, the first of which is an inequality constraint and the second of which is an equality constraint. These two constraints are hard constraints, meaning that it is required that they be satisfied; they define the feasible set of candidate solutions.
Without the constraints, the solution would be (0,0), where f(\bold x) has the lowest value. But this solution does not satisfy the constraints. The solution of the constrained optimization problem stated above is \bold x = (1,1), which is the point with the smallest value of f(\bold x) that satisfies the two constraints.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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